912 resultados para Agriwaste utilization


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Background & Objectives Emergency health services (EHS) throughout the world are increasingly congested. As more people use EHS, factors such as population growth and aging cannot fully explain this increase. Also, focus on patients’ clinical characteristics ignores the role that attitudinal and perceptual factors and motivations play in directing their decisions and actions. The aim of this study is to review and synthesize an integrated conceptual framework for understanding social psychological factors underpinning demand for EHS. Methodology A comprehensive search and review of empirical and theoretical studies about the utilization of EHS was conducted using major medical, health, social and behavioral sciences databases. Results A small number of studies used a relevant conceptual framework (e.g. Health Services Utilization Model or Health Belief Model) or their components to analyze patients’ decision to use EHS. The studies evidenced that demand was affected by perceived severity of the condition; perceived costs and benefits (e.g. availability, accessibility and affordability of alternative services); experience, preference and knowledge; perceived and actual social support; and demographic characteristics (e.g. age, sex, socioeconomic status, ethnicity, marital and living circumstances, place of residence). Conclusions Conceptual models that are commonly used in areas like social and behavioral sciences have rarely been applied in the EHS utilization field. Understanding patients’ decision-making and associated factors will lay the groundwork for identification of the evidence to inform improved policy responses and the development of demand management strategies. An integrated conceptual framework will be introduced as part of this study.

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Recent literature on Enterprise System (ES) implementation projects highlights the importance of Knowledge Integration (KI) for implementation success. The fundamental characteristics of ES - integration of modules, business process view, and aspects of information transparency - necessitate that all frequent end-users share a reasonable amount of common knowledge and integrate their knowledge to yield new knowledge. Unfortunately, the importance of KI is often overlooked and little about the role of KI in ES success is known. In this chapter, the authors study the KI impact on ES success that is relevant to the ES post-implementation in support of organizations' returns on their ES investments. They adopt the ES post-implementation segment of ES utilization to explore whether the KI approach is causally linked to ES success. The research model was tested in a multi-industry sample in Malaysia from which data was gathered from managerial and operational employees spread across six large organizations. Consistent with the explanation by knowledge-based theory, the results show that KI was valid and significantly related to the outcome of ES that relates to an organization's performance, which the authors refer to as ES success. The KI positive impact on the success of ES drives one to highlight the importance of ontological KI in the complexity of the ES environment. The authors believe that focusing on an ontology through the KI perspective can make significant contributions to current ES problems.

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Desalination is considered one of the most suitable areas for the utilization of solar energy, as there are many places in the world where abundant supply of solar energy is available and also there is a great demand for fresh water. An integrated solar heat pump desalination system has been developed at the National University of Singapore. The system also offers the opportunity of water heating and drying utilizing solar, ambient energy and waste heat from air conditioning system, which is conventionally dumped into the environment causing global warming. Desalination is carried out by making use of a single effect of Multi-Effect Distillation (MED) system. Within the desalination chamber, both fl ashing and evaporation of saline water take place. The maximum Coefficient of Performance (COP) of the heat pump system was around 5.8. In the integrated system, the maximum fresh water production rate was 9.6 l h−1 and a Performance Ratio (PR) of 1.2. For only desalination, the system has the potential to produce a maximum of 30 l h−1 of fresh water.

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This paper presents a grid-side inverter based supercapacitor direct integration scheme for wind power systems. The inverter used in this study consists of a conventional two-level inverter and three H-bridge modules. Three supercapacitor banks are directly connected to the dc-links of H-bridge modules. This approach eliminates the need for interfacing dc-dc converters and thus considerably improves the overall efficiency. However, for the maximum utilization of super capacitors their voltages should be allowed to vary. As a result of this variable voltage space vectors of the hybrid inverter get distributed unevenly. To handle this issue, a modified PWM method and a space vector modulation method are proposed and they can generate undistorted current even in the presence of unevenly distributed space vectors. A supercapacitor voltage balancing method is also presented in this paper. Simulation results are presented to validate the efficacy of the proposed scheme, modulation methods and control techniques.

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For robots operating in outdoor environments, a number of factors, including weather, time of day, rough terrain, high speeds, and hardware limitations, make performing vision-based simultaneous localization and mapping with current techniques infeasible due to factors such as image blur and/or underexposure, especially on smaller platforms and low-cost hardware. In this paper, we present novel visual place-recognition and odometry techniques that address the challenges posed by low lighting, perceptual change, and low-cost cameras. Our primary contribution is a novel two-step algorithm that combines fast low-resolution whole image matching with a higher-resolution patch-verification step, as well as image saliency methods that simultaneously improve performance and decrease computing time. The algorithms are demonstrated using consumer cameras mounted on a small vehicle in a mixed urban and vegetated environment and a car traversing highway and suburban streets, at different times of day and night and in various weather conditions. The algorithms achieve reliable mapping over the course of a day, both when incrementally incorporating new visual scenes from different times of day into an existing map, and when using a static map comprising visual scenes captured at only one point in time. Using the two-step place-recognition process, we demonstrate for the first time single-image, error-free place recognition at recall rates above 50% across a day-night dataset without prior training or utilization of image sequences. This place-recognition performance enables topologically correct mapping across day-night cycles.

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Traditional towns of the Kathmandu Valley boast a fine provision of public spaces in their neighbourhoods. Historically, a hierarchy of public space has been distributed over the entire town with each neighbourhood centered around more or less spacious public squares. However, rapid growth of these towns over the past decades has resulted in haphazard development of new urban areas with little provision of public space. Recent studies indicate that the loss of public space is a major consequence of the uncontrolled urban growth of the Kathmandu Valley and its new neighbourhoods. This paper reviews the current urban growth of the Kathmandu Valley and its impact on the development of public space in new neighbourhoods. The preliminary analysis of the case study of three new neighbourhoods shows that the formation and utilization of neighbourhood public space exhibit fundamental differences from those found in the traditional city cores. The following key issues are identified in this paper: a) Governance and regulations have been a challenge to regulate rapid urban growth; b) The current pattern of neighbourhood formation is found to be different from that of traditional neighbourhoods due to the changes with rapid urban development; c) Public spaces have been compromised in both planned and unplanned new neighbourhoods in terms of their quantity and quality; d) The changing provision of public space has contributed to its changing use and meaning; and e) The changing demographic composition, changing society and life style have had direct impact on the declining use of public space. Moreover, the management of public spaces remains a big challenge due to their changing nature and the changing governance. The current transformation public space does not appear to be conducive, and has led to adversely changing social environment of the new neighbourhoods.

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Research problem: Overfitting and collinearity problems commonly exist in current construction cost estimation applications and obstruct researchers and practitioners in achieving better modelling results. Research objective and method: A hybrid approach of Akaike information criterion (AIC) stepwise regression and principal component regression (PCR) is proposed to help solve overfitting and collinearity problems. Utilization of this approach in linear regression is validated by comparing it with other commonly used approaches. The mean square error obtained by leave-one-out cross validation (MSELOOCV) is used in model selection in deciding predictive variables.

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Background Osteoporosis is a common cause of disability and death in elderly men and women. Until 2007, Australian Government-subsidized use of oral bisphosphonates, raloxifene and calcitriol (1α,25-dihydroxycholecalciferol) was limited to secondary prevention (requiring x-ray evidence of previous low-trauma fracture). The cost to the Pharmaceutical Benefits Scheme was substantial (164 million Australian dollars in 2005/6). Objective To examine the dispensed prescriptions for oral bisphosphonates, raloxifene, calcitriol and two calcium products for the secondary prevention of osteoporosis (after previous low-trauma fracture) in the Australian population. Methods We analysed government data on prescriptions for oral bisphosphonates, raloxifene, calcitriol and two calcium products from 1995 to 2006, and by sex and age from 2002 to 2006. Prescription counts were converted to defined daily doses (DDD)/1000 population/day. This standardized drug utilization method used census population data, and adjusts for the effects of aging in the Australian population. Results Total bisphosphonate use increased 460% from 2.19 to 12.26 DDD/1000 population/day between June 2000 and June 2006. The proportion of total bisphosphonate use in June 2006 was 75.1% alendronate, 24.6% risedronate and 0.3% etidronate. Raloxifene use in June 2006 was 1.32 DDD/1000 population/day. The weekly forms of alendronate and risedronate, introduced in 2001 and 2003, respectively, were quickly adopted. Bisphosphonate use peaked at age 80–89 years in females and 85–94 years in males, with 3-fold higher use in females than in males. Conclusions Pharmaceutical intervention for osteoporosis in Australia is increasing with most use in the elderly, the population at greatest risk of fracture. However, fracture prevalence in this population is considerably higher than prescribing of effective anti-osteoporosis medications, representing a missed opportunity for the quality use of medicines.

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This paper challenges the assumptions underlying many reviews and offers alternative criteria for examining evidence for nonpharmacological interventions. We evaluated 27 reviews examining interventions for persons with dementia as they relate to the issues of selection based on randomized controlled trial (RCT) design. Reviews were described by type of intervention, level of cognitive function, and criteria for inclusion. Of the 27 reviews, 46% required RCTs for inclusion and most had stringent inclusion criteria. This resulted in poor utilization of the literature and low ecological validity. Eliminating most of the available data poses a critical problem to clinical and research development. Studies meeting strict methodological criteria may not generalize to the greater population or may exclude sub-populations and interventions. Limitations of double-blind RCTs and potential design solutions are set forth based on appropriate populations, problems, interventions, and settings characteristics.

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Objective This study examined whether maternal psychological distress mediates the relationship between presence of adolescent asthma and number of physician visits, and whether the association between maternal psychological distress and physician visits is moderated by adolescent general health. Methods Data were obtained from the Mater University Study of Pregnancy and included 4025 adolescents. Path analysis was used to examine mediating and moderating effects. Results Maternal psychological distress was found to partially mediate the relationship between adolescent asthma and number of physician visits, accounting for 25% of the effect of adolescent asthma on physician visits (p = .046). There was no evidence to suggest that adolescent general health moderated the association between maternal psychological distress and physician visits (p = .093). Conclusions The findings suggest that maternal psychological distress is associated with increased physician visits, regardless of adolescents' general health. Lowering maternal psychological distress may serve to reduce health care utilization and costs among adolescents with asthma.

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With the recent development of advanced metering infrastructure, real-time pricing (RTP) scheme is anticipated to be introduced in future retail electricity market. This paper proposes an algorithm for a home energy management scheduler (HEMS) to reduce the cost of energy consumption using RTP. The proposed algorithm works in three subsequent phases namely real-time monitoring (RTM), stochastic scheduling (STS) and real-time control (RTC). In RTM phase, characteristics of available controllable appliances are monitored in real-time and stored in HEMS. In STS phase, HEMS computes an optimal policy using stochastic dynamic programming (SDP) to select a set of appliances to be controlled with an objective of the total cost of energy consumption in a house. Finally, in RTC phase, HEMS initiates the control of the selected appliances. The proposed HEMS is unique as it intrinsically considers uncertainties in RTP and power consumption pattern of various appliances. In RTM phase, appliances are categorized according to their characteristics to ease the control process, thereby minimizing the number of control commands issued by HEMS. Simulation results validate the proposed method for HEMS.

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In the past few years, there has been a steady increase in the attention, importance and focus of green initiatives related to data centers. While various energy aware measures have been developed for data centers, the requirement of improving the performance efficiency of application assignment at the same time has yet to be fulfilled. For instance, many energy aware measures applied to data centers maintain a trade-off between energy consumption and Quality of Service (QoS). To address this problem, this paper presents a novel concept of profiling to facilitate offline optimization for a deterministic application assignment to virtual machines. Then, a profile-based model is established for obtaining near-optimal allocations of applications to virtual machines with consideration of three major objectives: energy cost, CPU utilization efficiency and application completion time. From this model, a profile-based and scalable matching algorithm is developed to solve the profile-based model. The assignment efficiency of our algorithm is then compared with that of the Hungarian algorithm, which does not scale well though giving the optimal solution.

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The aim of the study was to assess the feasibility and effectiveness of aquatic‐based exercise in the form of deep water running ( DWR ) as part of a multimodal physiotherapy programme ( MMPP ) for breast cancer survivors. A controlled clinical trial was conducted in 42 primary breast cancer survivors recruited from community‐based P rimary C are C entres. Patients in the experimental group received a MMPP incorporating DWR , 3 times a week, for an 8‐week period. The control group received a leaflet containing instructions to continue with normal activities. Statistically significant improvements and intergroup effect size were found for the experimental group for P iper F atigue S cale‐ R evised total score ( d = 0.7, P = 0.001), as well as behavioural/severity ( d = 0.6, P = 0.05), affective/meaning ( d = 1.0, P = 0.001) and sensory ( d = 0.3, P = 0.03) domains. Statistically significant differences between the experimental and control groups were also found for general health ( d = 0.5, P < 0.05) and quality of life ( d = 1.3, P < 0.05). All participants attended over 80% of sessions, with no major adverse events reported. The results of this study suggest MMPP incorporating DWR decreases cancer‐related fatigue and improves general health and quality of life in breast cancer survivors. Further, the high level of adherence and lack of adverse events indicate such a programme is safe and feasible.

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BACKGROUND The increasing cost of fossil fuels as well as the escalating social and industrial awareness of the environmental impacts associated with the use of fossil fuels has created the need for more sustainable fuel options. Bioethanol, produced from renewable biomass such as sugar and starch materials, is believed to be one of these options, and it is currently being harnessed extensively. However, the utilization of sugar and starch materials as feedstocks for bioethanol production creates a major competition with the food market in terms of land for cultivation, and this makes bioethanol from these sources economically less attractive. RESULT This study explores the suitability of microalgae (Chlorococum sp.) as a substrate for bioethanol production via yeast (Saccharomycesbayanus)under different fermentation conditions. Results show a maximum ethanol concentration of 3.83 g L -1 obtained from 10 g L-1 of lipid-extracted microalgae debris. CONCLUSION This productivity level (∼38% w/w), which is in keeping with that of current production systems endorses microalgae as a promising substrate for bioethanol production.